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AI-powered Unity development assistant running as an mcp Actor. Generate C# scripts, create shaders, query LLMs (GPT-4, Claude, Gemini), analyze code, and manage Unity Cloud Services - all through a simple API.
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Pay per event
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christopher athans crow
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3
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2
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12 hours ago
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You can access the Unity Ai Assistant programmatically from your own applications by using the Apify API. You can also choose the language preference from below. To use the Apify API, you’ll need an Apify account and your API token, found in Integrations settings in Apify Console.
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the shader (for create_shader)" }, "shaderType": { "title": "Shader Type", "enum": [ "Surface", "Unlit", "Lit" ], "type": "string", "description": "Type of shader", "default": "Lit" }, "renderPipeline": { "title": "Render Pipeline", "enum": [ "Built-in", "URP", "HDRP" ], "type": "string", "description": "Unity render pipeline", "default": "URP" }, "gameObjectName": { "title": "GameObject Name", "type": "string", "description": "Name of GameObject to analyze" }, "prefabName": { "title": "Prefab Name", "type": "string", "description": "Name of prefab to optimize" }, "targetPlatform": { "title": "Target Platform", "enum": [ "Windows", "macOS", "Linux", "Android", "iOS", "WebGL" ], "type": "string", "description": "Unity target platform", "default": "Windows" }, "llmModel": { "title": "LLM Model", "enum": [ "gpt-4", "gpt-3.5-turbo", "claude-3-opus", "claude-3-sonnet", "gemini-pro" ], "type": "string", "description": "Language model to use (for query_llm)", "default": "gpt-4" }, "llmPrompt": { "title": "LLM Prompt", "type": "string", "description": "Question or prompt for the LLM" }, "codeToAnalyze": { "title": "Code to Analyze", "type": "string", "description": "C# code to analyze or complete" }, "textToSpeak": { "title": "Text to Speak", "type": "string", "description": "Text to convert to speech" }, "textsToTranslate": { "title": "Texts to Translate", "type": "array", "description": "UI texts to translate" }, "targetLanguages": { "title": "Target Languages", "type": "array", "description": "Language codes to translate to", "items": { "type": "string" } }, "unityProjectId": { "title": "Unity Project ID", "type": "string", "description": "Unity Cloud Project ID (for cloud operations)" }, "openaiApiKey": { "title": "OpenAI API Key", "type": "string", "description": "OpenAI API key (optional, for LLM operations)" }, "anthropicApiKey": { "title": "Anthropic API Key", "type": "string", "description": "Anthropic API key (optional, for Claude)" }, "googleApiKey": { "title": "Google API Key", "type": "string", "description": "Google API key (optional, for Gemini)" } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } }}OpenAPI is a standard for designing and describing RESTful APIs, allowing developers to define API structure, endpoints, and data formats in a machine-readable way. It simplifies API development, integration, and documentation.
OpenAPI is effective when used with AI agents and GPTs by standardizing how these systems interact with various APIs, for reliable integrations and efficient communication.
By defining machine-readable API specifications, OpenAPI allows AI models like GPTs to understand and use varied data sources, improving accuracy. This accelerates development, reduces errors, and provides context-aware responses, making OpenAPI a core component for AI applications.
You can download the OpenAPI definitions for Unity Ai Assistant from the options below:
If you’d like to learn more about how OpenAPI powers GPTs, read our blog post.
You can also check out our other API clients: